Results 101 to 110 of about 123,391 (326)
Scale mixtures of Kotz–Dirichlet distributions
Journal of Multivariate Analysis, 2013 AbstractIn this paper, we first show that a k-dimensional Dirichlet random vector has independent components if and only if it is a Kotz Type I Dirichlet random vector. We then consider in detail the class of k-dimensional scale mixtures of Kotz–Dirichlet random vectors, which is a natural extension of the class of Kotz Type I random vectors.
N. Balakrishnan 0002, Enkelejd Hashorva
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Comparison of modelling approaches for liquid fluidized beds
The Canadian Journal of Chemical Engineering, EarlyView.Abstract This study presents a comparison of three promising numerical models for the detailed simulation of liquid–solid fluidized bed. These models differ in their treatment of the solid phase, ranging from treating each particle individually to treating the collection of particles as a continuum.
Andreu Bernad‐Serra +3 more
wiley +1 more source
IEEE AccessFederated Learning (FL) enables collaborative training of Machine Learning (ML) models across decentralized clients while preserving data privacy. One of the challenges that FL faces is when the clients’ data is not independent and identically ...
Daniel Mauricio Jimenez Gutierrez +3 more
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A Dirichlet-Multinomial Bayes Classifier for Disease Diagnosis with Microbial Compositions
mSphere, 2017 Dysbiosis of microbial communities is associated with various human diseases, raising the possibility of using microbial compositions as biomarkers for disease diagnosis.
Xiang Gao, Huaiying Lin, Qunfeng Dong
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On the sub-Gaussianity of the Beta and Dirichlet distributions
Electronic Communications in Probability, 2017 13 pages, 2 ...
Marchal, Olivier, Arbel, Julyan
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Partial identification with categorical data and nonignorable missing outcomes
Canadian Journal of Statistics, EarlyView.Abstract Nonignorable missing outcomes are common in real‐world datasets and often require strong parametric assumptions to achieve identification. These assumptions can be implausible or untestable, and so we may wish to forgo them in favour of partially identified models that narrow the set of a priori possible values to an identification region.
Daniel Daly‐Grafstein, Paul Gustafson
wiley +1 more source
Entropy, 2018 When constructing discrete (binned) distributions from samples of a data set, applications exist where it is desirable to assure that all bins of the sample distribution have nonzero probability.
Paul Darscheid, Anneli Guthke, Uwe Ehret
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Corporate Social Responsibility and Environmental Management, EarlyView.ABSTRACT Recent literature addressing ESG and risk has increased by 70% since mid‐2022, reflecting a growing interest in sustainable finance. Guided by the PRISMA flow diagram, this paper employs a hybrid systematic review methodology, combining bibliometric analysis with content analysis, to provide a comprehensive overview of the evolution of ESG and
Fahad Asmi, Alain Neher, Alfred Wong
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Bayesian and Quasi-Bayesian Estimators for Mutual Information from Discrete Data
Entropy, 2013 Mutual information (MI) quantifies the statistical dependency between a pair of random variables, and plays a central role in the analysis of engineering and biological systems.
Il Memming Park +2 more
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A reversal phenomenon in estimation based on multiple samples from the Poisson--Dirichlet distribution [PDF]
, 2018 Koji Tsukuda, Shuhei Mano
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